Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Wang, Ningnan"'
Social media bot detection has always been an arms race between advancements in machine learning bot detectors and adversarial bot strategies to evade detection. In this work, we bring the arms race to the next level by investigating the opportunitie
Externí odkaz:
http://arxiv.org/abs/2402.00371
Autor:
Feng, Shangbin, Tan, Zhaoxuan, Chen, Zilong, Wang, Ningnan, Yu, Peisheng, Zheng, Qinghua, Chang, Xiaojun, Luo, Minnan
Modeling the ideological perspectives of political actors is an essential task in computational political science with applications in many downstream tasks. Existing approaches are generally limited to textual data and voting records, while they neg
Externí odkaz:
http://arxiv.org/abs/2210.08362
Autor:
Feng, Shangbin, Tan, Zhaoxuan, Wan, Herun, Wang, Ningnan, Chen, Zilong, Zhang, Binchi, Zheng, Qinghua, Zhang, Wenqian, Lei, Zhenyu, Yang, Shujie, Feng, Xinshun, Zhang, Qingyue, Wang, Hongrui, Liu, Yuhan, Bai, Yuyang, Wang, Heng, Cai, Zijian, Wang, Yanbo, Zheng, Lijing, Ma, Zihan, Li, Jundong, Luo, Minnan
Twitter bot detection has become an increasingly important task to combat misinformation, facilitate social media moderation, and preserve the integrity of the online discourse. State-of-the-art bot detection methods generally leverage the graph stru
Externí odkaz:
http://arxiv.org/abs/2206.04564
Twitter bot detection is an important and challenging task. Existing bot detection measures fail to address the challenge of community and disguise, falling short of detecting bots that disguise as genuine users and attack collectively. To address th
Externí odkaz:
http://arxiv.org/abs/2106.13092
Twitter has become a major social media platform since its launching in 2006, while complaints about bot accounts have increased recently. Although extensive research efforts have been made, the state-of-the-art bot detection methods fall short of ge
Externí odkaz:
http://arxiv.org/abs/2106.13089
Twitter has become a vital social media platform while an ample amount of malicious Twitter bots exist and induce undesirable social effects. Successful Twitter bot detection proposals are generally supervised, which rely heavily on large-scale datas
Externí odkaz:
http://arxiv.org/abs/2106.13088